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The future societal bill: methodological alternatives
Futures 35 (2003) 25–36 www.elsevier.com/locate/futures
The future societal bill: methodological alternatives Emilio Fontela ∗ Universidad Autonoma of Madrid, Cantoblanca, 28049, Madrid, Spain
Abstract This paper first defines economic considerations on the societal bill, pointing to the importance of public choices to establish adequate shares for market and non-market processes. Futures research provides a substantial component for policy studies in this area. A description is made of the contribution of quantitative models related to demographic and social accounting, and their extensions. Beyond statistical modelling other future research methods processing expert opinions, are also described, including interpretive structural modelling and scenario writing. The paper suggests the need for a closer link between expert opinions and socio-demographic models as a priority for futures research. 2002 Elsevier Science Ltd. All rights reserved.
1. The economic characteristics of societal expenditure Human consumption of goods and services constitutes the final economic aim of all production activities. This consumption can take place at an individual level by acquisition of these goods and services in their respective markets at a given price that is both satisfactory to the consumer and to the producer. But consumption can also have non-market characteristics; it can be appropriated by the consumer free of charge or at a price below the eventual market price, in which case it is generally a result of public production of the corresponding goods and services. The total consumption of market and non-market goods and services by households is defined as ‘enlarged’ consumption in the economic literature [1] and as ‘final’ consumption in the new system of national accounts [2].
∗
Tel.: +34 913078736; fax: +34 913078034. E-mail address: [email protected] (E. Fontela).
0016-3287/02/$ - see front matter 2002 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0016-3287(02)00048-4
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E. Fontela / Futures 35 (2003) 25–36
The share of market or non-market supply of goods and services is a matter for public choice, as well as the use of taxes and subsidies to modify market prices. It is up to socio-political forces to decide if the price of tobacco is to be increased by specific taxes, if a subsidy is to decrease the price of milk, or if education is to be provided free of charge to all citizens. In the SNA-93 framework, governments produce both private services and public goods. ‘Private’ services are produced by governments (or by non-profit institutions) for the benefit of individual households, and can be appropriated by them: Education, Health, Social Security and Welfare, Sports, Recreation and Culture mainly fall in this category. ‘Public’ goods are collective services that cannot be charged to individuals according to their usage or the benefit they derive, and clearly correspond to market failures: Security and Defence, Law and Order, Regulation and Legislation, Environmental Protection, and basic R&D fall in this category. Households include in their disposable incomes the social benefits and contributions that they receive from government, and they use this disposable income either to consume (consumer’s expenditures) or to save. The concept of final consumption is then the sum of consumer’s expenditure and of the ‘transfers in kind’ constituted by the ‘private’ services produced by governments. Traditionally, at least in Europe, two main categories of final or enlarged consumption are considered to be part of ‘social expenditure’ and are expected to be partly delivered in non-market conditions: health and education. But the societal bill goes beyond the supply of services to consumers; it also includes income transfers that allow to keep a minimum capacity to consume by all households: they relate mainly to pensions, unemployment benefits and entitlements for the poor and the disabled, and, as mentioned earlier, are part of the disposable income that can be allocated to the different consumption expenditures or savings of the households. Thus, the concept of ‘public societal bill’ involves both interpersonal and intergenerational solidarity income transfers and the provision of some social services; it aims at preserving equality of opportunities and to bring some greater equality in income. The notion of Welfare State covers these aspects of societal expenditure as well as other questions related to the production of ‘public’ goods, as defined above. In the area of social services, the public supply in non-market conditions may be completed by a market supply: this is clearly the case for education and health. Public universities can coexist with private universities, public hospitals with private hospitals. The fact is that there is a growing need for these services and that an equilibrium is to be found between those that can be economically supported by effective demand and those that have to be made accessible to the population without taking into consideration individual buying capacities. In the context of enlarged consumption, both education and health have to be considered superior goods, in the sense that their need increases when other more basic needs are satisfied: the propensity to devote to them a share of discretionary income is high, and there is therefore a clear economic justification for the coexistence of market and non-market activities [3].
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Furthermore, both education and health services are rather labour intensive activities and most probably are to be considered good examples of ‘Baumol’s disease’ [4]. Their productivity grows less than the average productivity of the economy (and certainly less than the productivity of most manufacturing sectors) and therefore the relative unit costs and prices of both education and health should in most circumstances grow above average; in other words, the relative cost of universities or hospitals increases permanently, whether they are public or private, even if we were to suppose that private institutions could be better managed than public ones. In the long run, in principle, the private activities in both sectors should disappear as their relative prices could become unbearable to final users. This interesting result of ‘Baumol’s disease’, that explains the disappearance of other stagnant productivity activities such as tailors and shoemakers, is however to be corrected by two other factors: 앫 on one side, as superior goods, both health and education are rather inelastic to prices and incomes, do not have easily available substitutes, and the market demand remains high and growing despite their increasingly high relative prices; 앫 but, furthermore, public transfers appear to act in the direction of keeping prices below actual costs: many private educational or health institutions do receive additional finance from public entities, and also from non-profit institutions (e.g. foundations), in order to avoid an excessive discrimination between have and have-nots even in the case of market functioning institutions. Whether private or public, health and education, as superior goods, are increasing their share of total GDP in all countries, and this share is correlated to income: high income countries like the USA and Sweden, with sharply different social choices as to the role of public or private supply of these services, still devote very similar shares of GDP to them. In the area of interpersonal and intergenerational solidarity transfers, there is also scope for both private and public provision, but in this case the economic argument is necessarily different, as the need for pensions, unemployment benefits or social assistance is negatively correlated with income and with wealth, and this is why this type of expenditure, when undertaken by public institutions, has to be interpreted as a process of income redistribution, allowing for some form of minimum level of income of the entire population during its entire life time (of course, public expenditure in education, specially important for the young, and in health, specially relevant for the elderly, are partly related to this same social objective). As personal income increases, the capacity to save for the future while acquiring assets or contracting insurance schemes, allows for progressive privatization of this part of the societal bill, or for using individual capitalization as a way of financing contributions. From a societal point of view this process is particularly attractive if the return on capital (e.g. the interest rate) is above the rate of growth of population and of production. This explains the growing interest for insurance schemes in advanced industrial countries with stagnant or declining population and low longterm rates of growth.
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From the point of view of governments, the ‘societal bill’ includes all the expenditure incurred either in supplying some superior services such as health or education, or in providing social transfers for unemployment or old age. Both types of public expenditure have been growing very fast in Europe during the second half of the 20th century, obliging governments to continuously increase the level of taxation, a process that has lead to radical criticism of the Welfare State. Many political forces already consider that the increasing trend of social expenditure and income transfers cannot be maintained into the future, and even that in some cases, commitments already taken, such as those on pensions, are to be considered unsustainable. The necessary debate on the future role of the public and the private sector in providing the services and transfers of the Welfare State, requires the support of futures oriented research. There is probably no other area with such large requirements for policy studies helping to prepare public choices. From the point of view of futures methodology, this is also an ideal research area combining both quantitative modelling approaches, and more qualitative exploration of expert opinions. This paper does not attempt to make a comprehensive review of the literature that deals with the future of the societal bill; such is the abundance of studies at national and international levels that a review would require a major team research effort. The more limited objective of the paper is to identify some methodological developments that may be used in tackling this important futures research endeavour.
2. Research methods for the analysis of the future of social expenditure While at the concluding point of this section some proposals will be made concerning the necessary linkage between modelling and heuristic approaches, for the simplicity of presentation both will be analysed separately and subsequently. 2.1. Modelling the future of social expenditure 2.1.1. Demographic and social accounting Demographic projections are a well-established activity run by international organizations (mainly the UN) as well as national statistical offices; it deals essentially with quantified modelling of future population and age groups under given assumptions for birth rates, death rates and migrations. The alternative hypothesis adopted for the projections are often called ‘scenarios’ in the very restricted sense of sets of values for the exogenous variables in a model. Of course, birth rates depend on fertility rates by age, marriage rates, and other demographic variables, as well as economic factors (G. S. Becker pointed to the fact that having a baby is rather similar to buying a consumer durable); death rates depend on age structures, morbidity and mortality rates and other mainly economic or even political variables (e.g. wars), and the complexity of factors determining migrations is infinite. Therefore, considerable research has been devoted to improving the explanatory
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power of demographic models, and in general one can say that demographic projections are probably the more robust core of any long-term futures comprehensive quantitative study. In a 10–20 years horizon, there are few demographic surprises. The robustness of demographic projections comes from the fact that the stock component of population is generally very high in relation to the flows that come in and out of the stock, always considering our usual discrete time measure: the year. The amount of 14-year-old in 2001 that will constitute the 15-year-old group in 2001 is known with a high degree of certainty. This characteristic of reasonably stable stock-flow relations can be extended from population projections to other areas of socio-demographic change, such as employment, education, or health. Let us describe, for the purpose of modelling this entire area of socio-demographic projections, Stone’s demographic matrix [5]. From the row for our country in Table 1, we can see that: nt+1 ⫽ Si ⫹ b ⫽ Cnt ⫹ b
(1)
where i denotes the unit vector and C denotes a coefficient matrix obtained by dividing the elements in the columns of S by the corresponding element of nt: that is C ⫽ S–n⫺1 t .
(2)
Eq. (1) states that the closing stock vector, nt+1, is equal to the opening stock vector, nt, transformed by the transition matrix, C, plus the exogenous vector of new entrants, b. Table 1 A demographic matrix connecting the opening and closing stocks of year t with the flows during year t State at new year t+1
Outside world Our country:closing states Opening stocks
State at new year t Outside world
Our country:opening states
a b
d’ S
Closing stocks
nt+1
nt’
Symbols: a is a scalar, denotes the total number of individuals who both enter and leave ‘our country’ in the course of year t and so are not recorded in either the opening or the closing stock of that year. An example is a baby born during the year who dies before the end of it. b is a column vector, denotes the new entrants into ‘our country’, namely the births and immigrations of year 6, who survive to the end of the year. Individuals in this group are recorded in the closing stock but not in the opening stock. d’is a row vector (the prime superscript indicates transposition), denotes the leavers from ‘our country’, namely the deaths and emigrations of year t. Individuals in this group appear in the opening stock but not in the closing stock. S is a square matrix, denotes the survivors in ‘our country’ through year t, and these are recorded in both the opening and the closing stock. They are classified by their opening states in the columns and by their closing states in the rows. nt’ is a row vector, denoting the opening stock in each state, and nt+1, a column vector denoting the closing stock at t (=the opening stock at t+1).
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The framework is very general; what we can get out of it depends on what we put into it, that is on the categories, or states, into which S is divided. If the process is to be simple and capable of being represented by an absorbing Markov chain, it is necessary. (i) That the states should be so defined that the probabilities of moving from them to other states are independent of the path by which the states have been reached; (ii) that the population should be homogenous; and (iii) that the transition coefficients should be constant [6]. This very simple accounting system and the linear input–output model that accompanies it, are of great relevance in all socio-economic transition processes, in many different areas of social interest, such as education, employment, health, delinquency, and so on. A life sequence traces the changes of state from birth to death in some particular compartment of life; age changes with time in a perfectly regular way; other human characteristics like health or education change but not in such a regular way, and even some social behaviour may not change at all. In practice, the information required for the demographic and socio-economic accounts is to be found in Censuses that essentially measure stocks at a point in time (while, on the contrary, economic information is mostly concentrated on the estimation of flows of products or of incomes). Censuses are established every 10 years, and produce additional elements of interest for the study of relations between socio-demographic variables. Thus, they allow computing matrices such as those dealing with: 앫 age structure and educational attainment; 앫 industrial employment and occupations; 앫 occupations and educational attachment, for social groups identified by sex or household characteristics. In the approach of Stone’s matrices described above, transitions are examined separately for each characteristic such as educational attainment or occupations, but it is also possible to extend the models to include these other structural relations and combinations of the socio-demographic systems. In all cases, looking into the long-term future implies some extrapolation of the transition proportions of Stone’s matrices or of the structural coefficients of crossclassifications of human characteristics, and in these cases econometrics may help. Let us take as an example the case of a Swiss socio-demographic labour market model established on a yearly basis with Stone’s matrices and the following states: 앫 앫 앫 앫
wage-earner; self-employed; non-working; unemployed.
In this case, it is assumed that the probability of changing from a given initial state at the beginning of the year (e.g. wage earner) to another state at the end of
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the year (e.g. non-working) is a function of individual’s age, and can be estimated econometrically fitting to the available data a logistic function [7]. Supposing that we have the data available to estimate transition proportions and possibly their dynamic time behaviour, Stone’s matrix provides an appropriate framework for projecting the social characteristics of given age groups, and therefore, in direct relation with the issue of the long-term development of the societal bill, the expected evolution of the number of: 앫 students in the different components of the educational system; 앫 retired people or those in the working population; 앫 people with different diseases or requirements of health services (Fig. 1). Of course, for estimating future societal bills, to know the number of people that may possibly be recipient of education, health and pensions is not enough. Economic and financial aspects have to be taken into consideration [8]. In principle, modelling future education and health expenditure appears to be rather straightforward, using some average costs related to the number of people using different services, and again calling upon econometrics to establish, if possible, the trends in these coefficients. Modelling pensions raises some additional difficulties as, besides the purely sociodemographic factors, expenditure coefficients are even more dependent than the cost for education or health, on policies related to the eligibility ratio and to the average pension for beneficiary [9]. Besides pure quantitative exploration of future societal bills, economists have developed simulation instruments to test some alternatives of generational accounting [10]. In these models, accounts estimate the present value of taxes paid minus transfer payments received that individuals of different annual cohorts pay in general on average over their remaining lifetimes. The aim of these computations is to test changes in the fiscal burden and to help correct eventual imbalances. In general, the bulk of the activity on quantitative projecting future social expenditure is concentrated in public administration and deals mostly with the short and medium range, while the long term is increasingly a subject of interest for academic as well as for political debate.
Fig. 1.
Socio-demographic models for the social bill.
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Of particular relevance in the academic context are, besides the generational accounting modelling mentioned above, two other lines of research: 앫 the first deals with the use of social accounting matrices (SAMs) recording all flows between economic agents, including social transfers; SAMs provide the core for general equilibrium modelling (GEM) that, under given assumptions as to the behaviour of the agents, allow to test alternative equilibria corresponding to different institutional developments [11]; 앫 the second deals with the development of models explaining governments public spending as in a complete system of semi-aggregated expenditure functions, looking for a maximization of public welfare under budget constraints [3]. It is important to note that while socio-demographic models, including generational accounting, rely essentially on the dynamics of population change (and therefore use as initial units of accounts either individuals or households), SAMs and models of enlarged consumption have monetary incomes as initial unit of account. The links between the two approaches is obviously the fact that from the first group of models financial flows are to be computed using some form of unit price-costs, and in the second group of models households are identified by given socio-demographic or income characteristics, and can be again directly related to physical units. The approaches are indeed complementary and portray different aspects of the same reality, present or future. These, and other quantitative research instruments, should help to improve public decision-making processes once future needs have been analysed by socio-demographic models as those described above. 2.1.2. The futures approach and the societal bill There is little doubt that the societal bill and its intergenerational consequences constitute an issue of relevance for futures research, going beyond the quantitative explorations outlined in the preceding section. As a matter of fact, the future of the societal bill depends on social-political-economic and technological environments, with a complexity that can hardly be reflected by any socio-demographic or economic model. A list of common sense examples will clearly state the nature of the problem: 앫 fertility rates and birth rates are closely linked to cultural factors and reflect life styles: the decline of Spanish or Italian fertility rates in recent years cannot be explained by demographic structural changes or by economic growth rates; 앫 the life sequence education–work–retirement that characterized the latest stages of the industrial era, is ill-adapted to the information era; continuous education and continuous work coupled with continuous leisure time are challenging the traditional model (and consequently the fundamental characteristics of the needs for education and income transfers) [12]; 앫 technology (bio-technologies, genetic engineering, information technologies, etc.) is continuously modifying the provision of health services;
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앫 and a long etc. Changes in complex environments require futures research approaches that combine knowledge of very different fields, besides the knowledge of demographers and economists that is currently concentrated in existing quantitative models. Of particular relevance for the treatment of complexity is the method of interpretative structural modelling (ISM) proposed by Warfield [13], leading to a matrix of logical multidimensional components of a given problem and of their relations. As pointed out by Ando and Fisher [14], ‘the variables taken as given by one discipline are the key subject matter of another and vice versa’. Structural analysis is therefore a learning effort from partial and dispersed knowledge, and the insights gained by structuring may be a sufficient justification for engaging in it. Any intellectual endeavour related to the future role of government and of its relation with households and enterprises requires a transparent process of structuring, in order to identify the drivers of change and their connections. The simple fact that in responding to the societal bill issue, governments may take options as different as those of Sweden and the USA, and still enjoy rather similar economic conditions in terms of level and growth of income or employment clearly shows that many solutions are possible to this complex issue and that any effort to understand the real alternatives for the future requires a multidimensional analysis of psychological factors (such as those related with the propensity of risk taking, or with the notion of solidarity inside and outside the family), social factors (such as the importance given to equality of opportunities or of incomes), political factors (such as the degree of democratic direct participation in collective decision-making) or other economic factors (such as the degree of enterprise concentration, or the size of self-employed). Structural analysis should help to make explicit, with matrices and graphs relating independent elements, the perception that many observers have of this complex system, thus opening the door to scenario writing, the most powerful tool of futures research [15]. The origin of the word Scenario is to be found in the French concept of a theatre play: the ‘scenario’ is indeed the script of the play, and of course an essential task for the writer of this script consists in developing a consistent view of the plot. The actors develop their personalities and their behaviours when confronted to the complexity of the plot. Constructing scenarios is a learning process starting with the drivers and trends of the recent past, their interrelation as identified by structural analysis, and the identification of the agents involved and of their decision-making power. Scenarios proceed from the present into the future exploring sets of alternatives concerning trends, possible events and agents behaviour when confronting new situations. Of course, this concept of scenario is multidimensional and is much broader that the concept of scenario often used in computer simulation of models: in this later case a scenario only refers to values of the exogenous variables contemplated and, of course, factors not included in these variables are to be considered irrelevant. Expert opinion may be of great utility when building scenarios both in the broad
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and in the narrow senses of the word. Experts that have acquired a good understanding of some of the central processes involved (such as those of psychological, social, political or economic factors mentioned above) certainly have mental models of the future, that are not sufficiently consolidated for detailed formalization. One of the main tasks of futures research is to call upon these latent mental models for improving the knowledge base of scenarios. This is the sense of Delphi techniques, and especially of cross-impact probabilistic methods [16,17]. The greatest difficulty to be faced in the elaboration of scenarios of alternative pictures for any given issue, such as the societal bill, stays with the fact that rapidly the factors considered reach a global level. The future of the societal bill in any European country cannot be made fully independent from the process of deepening and broadening of the EU, or from pressures of international competitiveness. The alternative futures that may be studied for Europe have indeed alternative societal bills, different roles for private or public education, health or pension schemes, different concepts of institutional diversity [18]. There is no example in recent years of a comprehensive scenario writing directly relevant for the study of the future of the societal bill in the EU. While quantitative modelling has grown as part of an overall debate on the costs and benefits of the Welfare State, the more fundamental problem of exploring coherent alternative systems has been, for the moment, left behind, and is only recently starting to receive due attention [19]. For improving decision-making processes in this area, it should be necessary to combine broad scenario writing with socio-demographic and economic modelling, thus establishing a bridge between futures researchers and model builders, that, in recent years, and in particular after the controversy on the Club of Rome’s Limits to Growth, have shown increasingly divergent paths [20].
3. Concluding remarks While it is clear that research is needed to explore coherently and exhaustively future social systems and societal bills, some ideas can already be deducted from the bulk of available partial studies: 앫 the European population is ageing, and this necessarily increases the relative importance of health care and pensions; in a decade, in Europe, ageing could add as much as 10% to the health bill; pensions may grow by an additional 3–4% of GDP in the next 30 years, but the increase will not yet be significant during the next decade, leaving a ‘breathing space’ for policy making [19]; 앫 education is a superior good, and is expected to play an increasing and continuous role in the information society; 앫 as income levels increase, the amount of discretionary income available for the acquisition of superior goods or of economic and financial assets increases, thus allowing for a greater private participation in the total societal expenditure on
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education, health and pensions, and for a decrease of the share of public provision of these services; 앫 with a greater role for private supply and markets in areas of the societal bill, social inequalities may increase, thus requiring new complementary forms of income redistribution (including alternative schemes as minimum guaranteed income, or negative tax proposals). The societal bill is a matter of social choice; there is a trade-off between market and non-market mechanisms, directly linked to income redistribution. Solidarity is an ethical social value. For any given level of equality, the public non-market share of production of the services of the social bill can be increased or decreased if, on the inverse, income redistribution is decreased or increased. Both are different forms of transfers, and transfers are the main component of solidarity. It is clear from simple inspection of the EU, that nations, societies, can take very different roads to solidarity and can be looking for very different levels of equality. It is up to futures research to provide ‘best knowledge available’ to this macro-process of societal choice.
References [1] Solari L, du Pasquier JN, editors. Private and enlarged consumption: essays in methodology and empirical analysis. Amsterdam: North Holland; 1976. [2] SNA-93, United Nations, Eurostat, IMF, OECD, World Bank. System of National Accounts. Brussels, N.Y., Paris, Wahsington, 1993. [3] Rossier ES, du Pasquier JN, editors. Sur le comportement de consommation de l’Etat dans le cadre de la the´ orie des choix. Amsterdam: North Holland; 1976. [4] Baumol WJ. Macroeconomics of unbalanced growth, the anatomy of urban crisis. Am Econ Rev 1967;57:415–26. [5] Stone R. The fundamental matrix of the active sequence. In: Brody A, Carter AP, editors. Input– output techniques. London: North Holland; 1972. [6] Stone R. Transition and admission models in social demography. Soc Sci Res 1973;2(2). [7] Aeschimann G et al. Modelling and forecasting the social contributions to the Swiss old age and survivor insurance scheme. Swiss J Econ Stat 1999;135(3):349–68. [8] Franco D, Munzi T. Ageing and fiscal policies in the European Union. In: Buti M, Franco D, Pench LR, editors. The welfare state in Europe. Cheltenham: Edward Elgan; 1999. [9] OECD. Reforming public pensions. Paris: OECD, 1988. [10] Kotlikoff LJ, Liebfritz W. An international comparison of generational accounts. SP 6447. Cambridge, MA: NBER, 1998. [11] Ginsburg V, Keyzer M. The structure of applied general equilibrium models. Cambridge, MA: MIT Press, 1997. [12] Giarini O, Liedtke PM. The employment dilemma: the future of work, Spanish edn, El dilema del empleo - El futuro del trabajo. Bilbao: Fundacio´ n Bilbao Bizkaia Kutxa, 1996. [13] Warfield JNS. Societal systems, planning, policy and complexity. New York: Wiley, 1976. [14] Ando A, Fisher FM. Two theorems on coeteris paribus in the analysis of dynamic systems. In: Ando A, Fisher FM, editors. Essays on the structure of social science models. Cambridge: MIT; 1963. [15] Godet M et al. Scenarios and strategies, a toolbox for problem-solving. LIPS working papers. Paris: CNAM, 1997. [16] Fontela E, Gabus A. Events and economic forecasting models. Futures 1974;6(4):329–33.
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[17] Duval A, Fontela E, Gabus A. Cross-impact analysis: a handbook on concepts and applications. Portraits of Complexity, Battelle Memorial Institute, monography No. 9, 1975. [18] Bertrand G, Michalski A, Pench L. Scenarios Europe 2010: five possible futures for Europe. Forward Studies Unit, EC, working paper, July 1999. [19] Fahrenkrog G et al. The societal bill: financing social protection and a sustainable environment. IPTS Futures Project. Seville: EC-JRC, 1999. [20] Fontela E. Bridging the gap between scenarios and models. Foresight 2000;2(1):10–4.
The future societal bill: methodological alternatives Emilio Fontela ∗ Universidad Autonoma of Madrid, Cantoblanca, 28049, Madrid, Spain
Abstract This paper first defines economic considerations on the societal bill, pointing to the importance of public choices to establish adequate shares for market and non-market processes. Futures research provides a substantial component for policy studies in this area. A description is made of the contribution of quantitative models related to demographic and social accounting, and their extensions. Beyond statistical modelling other future research methods processing expert opinions, are also described, including interpretive structural modelling and scenario writing. The paper suggests the need for a closer link between expert opinions and socio-demographic models as a priority for futures research. 2002 Elsevier Science Ltd. All rights reserved.
1. The economic characteristics of societal expenditure Human consumption of goods and services constitutes the final economic aim of all production activities. This consumption can take place at an individual level by acquisition of these goods and services in their respective markets at a given price that is both satisfactory to the consumer and to the producer. But consumption can also have non-market characteristics; it can be appropriated by the consumer free of charge or at a price below the eventual market price, in which case it is generally a result of public production of the corresponding goods and services. The total consumption of market and non-market goods and services by households is defined as ‘enlarged’ consumption in the economic literature [1] and as ‘final’ consumption in the new system of national accounts [2].
∗
Tel.: +34 913078736; fax: +34 913078034. E-mail address: [email protected] (E. Fontela).
0016-3287/02/$ - see front matter 2002 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0016-3287(02)00048-4
26
E. Fontela / Futures 35 (2003) 25–36
The share of market or non-market supply of goods and services is a matter for public choice, as well as the use of taxes and subsidies to modify market prices. It is up to socio-political forces to decide if the price of tobacco is to be increased by specific taxes, if a subsidy is to decrease the price of milk, or if education is to be provided free of charge to all citizens. In the SNA-93 framework, governments produce both private services and public goods. ‘Private’ services are produced by governments (or by non-profit institutions) for the benefit of individual households, and can be appropriated by them: Education, Health, Social Security and Welfare, Sports, Recreation and Culture mainly fall in this category. ‘Public’ goods are collective services that cannot be charged to individuals according to their usage or the benefit they derive, and clearly correspond to market failures: Security and Defence, Law and Order, Regulation and Legislation, Environmental Protection, and basic R&D fall in this category. Households include in their disposable incomes the social benefits and contributions that they receive from government, and they use this disposable income either to consume (consumer’s expenditures) or to save. The concept of final consumption is then the sum of consumer’s expenditure and of the ‘transfers in kind’ constituted by the ‘private’ services produced by governments. Traditionally, at least in Europe, two main categories of final or enlarged consumption are considered to be part of ‘social expenditure’ and are expected to be partly delivered in non-market conditions: health and education. But the societal bill goes beyond the supply of services to consumers; it also includes income transfers that allow to keep a minimum capacity to consume by all households: they relate mainly to pensions, unemployment benefits and entitlements for the poor and the disabled, and, as mentioned earlier, are part of the disposable income that can be allocated to the different consumption expenditures or savings of the households. Thus, the concept of ‘public societal bill’ involves both interpersonal and intergenerational solidarity income transfers and the provision of some social services; it aims at preserving equality of opportunities and to bring some greater equality in income. The notion of Welfare State covers these aspects of societal expenditure as well as other questions related to the production of ‘public’ goods, as defined above. In the area of social services, the public supply in non-market conditions may be completed by a market supply: this is clearly the case for education and health. Public universities can coexist with private universities, public hospitals with private hospitals. The fact is that there is a growing need for these services and that an equilibrium is to be found between those that can be economically supported by effective demand and those that have to be made accessible to the population without taking into consideration individual buying capacities. In the context of enlarged consumption, both education and health have to be considered superior goods, in the sense that their need increases when other more basic needs are satisfied: the propensity to devote to them a share of discretionary income is high, and there is therefore a clear economic justification for the coexistence of market and non-market activities [3].
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Furthermore, both education and health services are rather labour intensive activities and most probably are to be considered good examples of ‘Baumol’s disease’ [4]. Their productivity grows less than the average productivity of the economy (and certainly less than the productivity of most manufacturing sectors) and therefore the relative unit costs and prices of both education and health should in most circumstances grow above average; in other words, the relative cost of universities or hospitals increases permanently, whether they are public or private, even if we were to suppose that private institutions could be better managed than public ones. In the long run, in principle, the private activities in both sectors should disappear as their relative prices could become unbearable to final users. This interesting result of ‘Baumol’s disease’, that explains the disappearance of other stagnant productivity activities such as tailors and shoemakers, is however to be corrected by two other factors: 앫 on one side, as superior goods, both health and education are rather inelastic to prices and incomes, do not have easily available substitutes, and the market demand remains high and growing despite their increasingly high relative prices; 앫 but, furthermore, public transfers appear to act in the direction of keeping prices below actual costs: many private educational or health institutions do receive additional finance from public entities, and also from non-profit institutions (e.g. foundations), in order to avoid an excessive discrimination between have and have-nots even in the case of market functioning institutions. Whether private or public, health and education, as superior goods, are increasing their share of total GDP in all countries, and this share is correlated to income: high income countries like the USA and Sweden, with sharply different social choices as to the role of public or private supply of these services, still devote very similar shares of GDP to them. In the area of interpersonal and intergenerational solidarity transfers, there is also scope for both private and public provision, but in this case the economic argument is necessarily different, as the need for pensions, unemployment benefits or social assistance is negatively correlated with income and with wealth, and this is why this type of expenditure, when undertaken by public institutions, has to be interpreted as a process of income redistribution, allowing for some form of minimum level of income of the entire population during its entire life time (of course, public expenditure in education, specially important for the young, and in health, specially relevant for the elderly, are partly related to this same social objective). As personal income increases, the capacity to save for the future while acquiring assets or contracting insurance schemes, allows for progressive privatization of this part of the societal bill, or for using individual capitalization as a way of financing contributions. From a societal point of view this process is particularly attractive if the return on capital (e.g. the interest rate) is above the rate of growth of population and of production. This explains the growing interest for insurance schemes in advanced industrial countries with stagnant or declining population and low longterm rates of growth.
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From the point of view of governments, the ‘societal bill’ includes all the expenditure incurred either in supplying some superior services such as health or education, or in providing social transfers for unemployment or old age. Both types of public expenditure have been growing very fast in Europe during the second half of the 20th century, obliging governments to continuously increase the level of taxation, a process that has lead to radical criticism of the Welfare State. Many political forces already consider that the increasing trend of social expenditure and income transfers cannot be maintained into the future, and even that in some cases, commitments already taken, such as those on pensions, are to be considered unsustainable. The necessary debate on the future role of the public and the private sector in providing the services and transfers of the Welfare State, requires the support of futures oriented research. There is probably no other area with such large requirements for policy studies helping to prepare public choices. From the point of view of futures methodology, this is also an ideal research area combining both quantitative modelling approaches, and more qualitative exploration of expert opinions. This paper does not attempt to make a comprehensive review of the literature that deals with the future of the societal bill; such is the abundance of studies at national and international levels that a review would require a major team research effort. The more limited objective of the paper is to identify some methodological developments that may be used in tackling this important futures research endeavour.
2. Research methods for the analysis of the future of social expenditure While at the concluding point of this section some proposals will be made concerning the necessary linkage between modelling and heuristic approaches, for the simplicity of presentation both will be analysed separately and subsequently. 2.1. Modelling the future of social expenditure 2.1.1. Demographic and social accounting Demographic projections are a well-established activity run by international organizations (mainly the UN) as well as national statistical offices; it deals essentially with quantified modelling of future population and age groups under given assumptions for birth rates, death rates and migrations. The alternative hypothesis adopted for the projections are often called ‘scenarios’ in the very restricted sense of sets of values for the exogenous variables in a model. Of course, birth rates depend on fertility rates by age, marriage rates, and other demographic variables, as well as economic factors (G. S. Becker pointed to the fact that having a baby is rather similar to buying a consumer durable); death rates depend on age structures, morbidity and mortality rates and other mainly economic or even political variables (e.g. wars), and the complexity of factors determining migrations is infinite. Therefore, considerable research has been devoted to improving the explanatory
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power of demographic models, and in general one can say that demographic projections are probably the more robust core of any long-term futures comprehensive quantitative study. In a 10–20 years horizon, there are few demographic surprises. The robustness of demographic projections comes from the fact that the stock component of population is generally very high in relation to the flows that come in and out of the stock, always considering our usual discrete time measure: the year. The amount of 14-year-old in 2001 that will constitute the 15-year-old group in 2001 is known with a high degree of certainty. This characteristic of reasonably stable stock-flow relations can be extended from population projections to other areas of socio-demographic change, such as employment, education, or health. Let us describe, for the purpose of modelling this entire area of socio-demographic projections, Stone’s demographic matrix [5]. From the row for our country in Table 1, we can see that: nt+1 ⫽ Si ⫹ b ⫽ Cnt ⫹ b
(1)
where i denotes the unit vector and C denotes a coefficient matrix obtained by dividing the elements in the columns of S by the corresponding element of nt: that is C ⫽ S–n⫺1 t .
(2)
Eq. (1) states that the closing stock vector, nt+1, is equal to the opening stock vector, nt, transformed by the transition matrix, C, plus the exogenous vector of new entrants, b. Table 1 A demographic matrix connecting the opening and closing stocks of year t with the flows during year t State at new year t+1
Outside world Our country:closing states Opening stocks
State at new year t Outside world
Our country:opening states
a b
d’ S
Closing stocks
nt+1
nt’
Symbols: a is a scalar, denotes the total number of individuals who both enter and leave ‘our country’ in the course of year t and so are not recorded in either the opening or the closing stock of that year. An example is a baby born during the year who dies before the end of it. b is a column vector, denotes the new entrants into ‘our country’, namely the births and immigrations of year 6, who survive to the end of the year. Individuals in this group are recorded in the closing stock but not in the opening stock. d’is a row vector (the prime superscript indicates transposition), denotes the leavers from ‘our country’, namely the deaths and emigrations of year t. Individuals in this group appear in the opening stock but not in the closing stock. S is a square matrix, denotes the survivors in ‘our country’ through year t, and these are recorded in both the opening and the closing stock. They are classified by their opening states in the columns and by their closing states in the rows. nt’ is a row vector, denoting the opening stock in each state, and nt+1, a column vector denoting the closing stock at t (=the opening stock at t+1).
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The framework is very general; what we can get out of it depends on what we put into it, that is on the categories, or states, into which S is divided. If the process is to be simple and capable of being represented by an absorbing Markov chain, it is necessary. (i) That the states should be so defined that the probabilities of moving from them to other states are independent of the path by which the states have been reached; (ii) that the population should be homogenous; and (iii) that the transition coefficients should be constant [6]. This very simple accounting system and the linear input–output model that accompanies it, are of great relevance in all socio-economic transition processes, in many different areas of social interest, such as education, employment, health, delinquency, and so on. A life sequence traces the changes of state from birth to death in some particular compartment of life; age changes with time in a perfectly regular way; other human characteristics like health or education change but not in such a regular way, and even some social behaviour may not change at all. In practice, the information required for the demographic and socio-economic accounts is to be found in Censuses that essentially measure stocks at a point in time (while, on the contrary, economic information is mostly concentrated on the estimation of flows of products or of incomes). Censuses are established every 10 years, and produce additional elements of interest for the study of relations between socio-demographic variables. Thus, they allow computing matrices such as those dealing with: 앫 age structure and educational attainment; 앫 industrial employment and occupations; 앫 occupations and educational attachment, for social groups identified by sex or household characteristics. In the approach of Stone’s matrices described above, transitions are examined separately for each characteristic such as educational attainment or occupations, but it is also possible to extend the models to include these other structural relations and combinations of the socio-demographic systems. In all cases, looking into the long-term future implies some extrapolation of the transition proportions of Stone’s matrices or of the structural coefficients of crossclassifications of human characteristics, and in these cases econometrics may help. Let us take as an example the case of a Swiss socio-demographic labour market model established on a yearly basis with Stone’s matrices and the following states: 앫 앫 앫 앫
wage-earner; self-employed; non-working; unemployed.
In this case, it is assumed that the probability of changing from a given initial state at the beginning of the year (e.g. wage earner) to another state at the end of
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the year (e.g. non-working) is a function of individual’s age, and can be estimated econometrically fitting to the available data a logistic function [7]. Supposing that we have the data available to estimate transition proportions and possibly their dynamic time behaviour, Stone’s matrix provides an appropriate framework for projecting the social characteristics of given age groups, and therefore, in direct relation with the issue of the long-term development of the societal bill, the expected evolution of the number of: 앫 students in the different components of the educational system; 앫 retired people or those in the working population; 앫 people with different diseases or requirements of health services (Fig. 1). Of course, for estimating future societal bills, to know the number of people that may possibly be recipient of education, health and pensions is not enough. Economic and financial aspects have to be taken into consideration [8]. In principle, modelling future education and health expenditure appears to be rather straightforward, using some average costs related to the number of people using different services, and again calling upon econometrics to establish, if possible, the trends in these coefficients. Modelling pensions raises some additional difficulties as, besides the purely sociodemographic factors, expenditure coefficients are even more dependent than the cost for education or health, on policies related to the eligibility ratio and to the average pension for beneficiary [9]. Besides pure quantitative exploration of future societal bills, economists have developed simulation instruments to test some alternatives of generational accounting [10]. In these models, accounts estimate the present value of taxes paid minus transfer payments received that individuals of different annual cohorts pay in general on average over their remaining lifetimes. The aim of these computations is to test changes in the fiscal burden and to help correct eventual imbalances. In general, the bulk of the activity on quantitative projecting future social expenditure is concentrated in public administration and deals mostly with the short and medium range, while the long term is increasingly a subject of interest for academic as well as for political debate.
Fig. 1.
Socio-demographic models for the social bill.
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Of particular relevance in the academic context are, besides the generational accounting modelling mentioned above, two other lines of research: 앫 the first deals with the use of social accounting matrices (SAMs) recording all flows between economic agents, including social transfers; SAMs provide the core for general equilibrium modelling (GEM) that, under given assumptions as to the behaviour of the agents, allow to test alternative equilibria corresponding to different institutional developments [11]; 앫 the second deals with the development of models explaining governments public spending as in a complete system of semi-aggregated expenditure functions, looking for a maximization of public welfare under budget constraints [3]. It is important to note that while socio-demographic models, including generational accounting, rely essentially on the dynamics of population change (and therefore use as initial units of accounts either individuals or households), SAMs and models of enlarged consumption have monetary incomes as initial unit of account. The links between the two approaches is obviously the fact that from the first group of models financial flows are to be computed using some form of unit price-costs, and in the second group of models households are identified by given socio-demographic or income characteristics, and can be again directly related to physical units. The approaches are indeed complementary and portray different aspects of the same reality, present or future. These, and other quantitative research instruments, should help to improve public decision-making processes once future needs have been analysed by socio-demographic models as those described above. 2.1.2. The futures approach and the societal bill There is little doubt that the societal bill and its intergenerational consequences constitute an issue of relevance for futures research, going beyond the quantitative explorations outlined in the preceding section. As a matter of fact, the future of the societal bill depends on social-political-economic and technological environments, with a complexity that can hardly be reflected by any socio-demographic or economic model. A list of common sense examples will clearly state the nature of the problem: 앫 fertility rates and birth rates are closely linked to cultural factors and reflect life styles: the decline of Spanish or Italian fertility rates in recent years cannot be explained by demographic structural changes or by economic growth rates; 앫 the life sequence education–work–retirement that characterized the latest stages of the industrial era, is ill-adapted to the information era; continuous education and continuous work coupled with continuous leisure time are challenging the traditional model (and consequently the fundamental characteristics of the needs for education and income transfers) [12]; 앫 technology (bio-technologies, genetic engineering, information technologies, etc.) is continuously modifying the provision of health services;
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앫 and a long etc. Changes in complex environments require futures research approaches that combine knowledge of very different fields, besides the knowledge of demographers and economists that is currently concentrated in existing quantitative models. Of particular relevance for the treatment of complexity is the method of interpretative structural modelling (ISM) proposed by Warfield [13], leading to a matrix of logical multidimensional components of a given problem and of their relations. As pointed out by Ando and Fisher [14], ‘the variables taken as given by one discipline are the key subject matter of another and vice versa’. Structural analysis is therefore a learning effort from partial and dispersed knowledge, and the insights gained by structuring may be a sufficient justification for engaging in it. Any intellectual endeavour related to the future role of government and of its relation with households and enterprises requires a transparent process of structuring, in order to identify the drivers of change and their connections. The simple fact that in responding to the societal bill issue, governments may take options as different as those of Sweden and the USA, and still enjoy rather similar economic conditions in terms of level and growth of income or employment clearly shows that many solutions are possible to this complex issue and that any effort to understand the real alternatives for the future requires a multidimensional analysis of psychological factors (such as those related with the propensity of risk taking, or with the notion of solidarity inside and outside the family), social factors (such as the importance given to equality of opportunities or of incomes), political factors (such as the degree of democratic direct participation in collective decision-making) or other economic factors (such as the degree of enterprise concentration, or the size of self-employed). Structural analysis should help to make explicit, with matrices and graphs relating independent elements, the perception that many observers have of this complex system, thus opening the door to scenario writing, the most powerful tool of futures research [15]. The origin of the word Scenario is to be found in the French concept of a theatre play: the ‘scenario’ is indeed the script of the play, and of course an essential task for the writer of this script consists in developing a consistent view of the plot. The actors develop their personalities and their behaviours when confronted to the complexity of the plot. Constructing scenarios is a learning process starting with the drivers and trends of the recent past, their interrelation as identified by structural analysis, and the identification of the agents involved and of their decision-making power. Scenarios proceed from the present into the future exploring sets of alternatives concerning trends, possible events and agents behaviour when confronting new situations. Of course, this concept of scenario is multidimensional and is much broader that the concept of scenario often used in computer simulation of models: in this later case a scenario only refers to values of the exogenous variables contemplated and, of course, factors not included in these variables are to be considered irrelevant. Expert opinion may be of great utility when building scenarios both in the broad
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and in the narrow senses of the word. Experts that have acquired a good understanding of some of the central processes involved (such as those of psychological, social, political or economic factors mentioned above) certainly have mental models of the future, that are not sufficiently consolidated for detailed formalization. One of the main tasks of futures research is to call upon these latent mental models for improving the knowledge base of scenarios. This is the sense of Delphi techniques, and especially of cross-impact probabilistic methods [16,17]. The greatest difficulty to be faced in the elaboration of scenarios of alternative pictures for any given issue, such as the societal bill, stays with the fact that rapidly the factors considered reach a global level. The future of the societal bill in any European country cannot be made fully independent from the process of deepening and broadening of the EU, or from pressures of international competitiveness. The alternative futures that may be studied for Europe have indeed alternative societal bills, different roles for private or public education, health or pension schemes, different concepts of institutional diversity [18]. There is no example in recent years of a comprehensive scenario writing directly relevant for the study of the future of the societal bill in the EU. While quantitative modelling has grown as part of an overall debate on the costs and benefits of the Welfare State, the more fundamental problem of exploring coherent alternative systems has been, for the moment, left behind, and is only recently starting to receive due attention [19]. For improving decision-making processes in this area, it should be necessary to combine broad scenario writing with socio-demographic and economic modelling, thus establishing a bridge between futures researchers and model builders, that, in recent years, and in particular after the controversy on the Club of Rome’s Limits to Growth, have shown increasingly divergent paths [20].
3. Concluding remarks While it is clear that research is needed to explore coherently and exhaustively future social systems and societal bills, some ideas can already be deducted from the bulk of available partial studies: 앫 the European population is ageing, and this necessarily increases the relative importance of health care and pensions; in a decade, in Europe, ageing could add as much as 10% to the health bill; pensions may grow by an additional 3–4% of GDP in the next 30 years, but the increase will not yet be significant during the next decade, leaving a ‘breathing space’ for policy making [19]; 앫 education is a superior good, and is expected to play an increasing and continuous role in the information society; 앫 as income levels increase, the amount of discretionary income available for the acquisition of superior goods or of economic and financial assets increases, thus allowing for a greater private participation in the total societal expenditure on
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education, health and pensions, and for a decrease of the share of public provision of these services; 앫 with a greater role for private supply and markets in areas of the societal bill, social inequalities may increase, thus requiring new complementary forms of income redistribution (including alternative schemes as minimum guaranteed income, or negative tax proposals). The societal bill is a matter of social choice; there is a trade-off between market and non-market mechanisms, directly linked to income redistribution. Solidarity is an ethical social value. For any given level of equality, the public non-market share of production of the services of the social bill can be increased or decreased if, on the inverse, income redistribution is decreased or increased. Both are different forms of transfers, and transfers are the main component of solidarity. It is clear from simple inspection of the EU, that nations, societies, can take very different roads to solidarity and can be looking for very different levels of equality. It is up to futures research to provide ‘best knowledge available’ to this macro-process of societal choice.
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[17] Duval A, Fontela E, Gabus A. Cross-impact analysis: a handbook on concepts and applications. Portraits of Complexity, Battelle Memorial Institute, monography No. 9, 1975. [18] Bertrand G, Michalski A, Pench L. Scenarios Europe 2010: five possible futures for Europe. Forward Studies Unit, EC, working paper, July 1999. [19] Fahrenkrog G et al. The societal bill: financing social protection and a sustainable environment. IPTS Futures Project. Seville: EC-JRC, 1999. [20] Fontela E. Bridging the gap between scenarios and models. Foresight 2000;2(1):10–4.